2 citations · 8 across the 15 of their papers we have counts for
10 papers · 1 filter
Towards Scalable and Cross-Lingual Specialist Language Models for Oncology
Morteza Rohanian, Tarun Mehra, Nicola Miglino +3
Clinical oncology generates vast, unstructured data that often contain inconsistencies, missing information, and ambiguities, making it difficult to extract reliable insights for d…
Uncertainty Modeling in Multimodal Speech Analysis Across the Psychosis Spectrum
Morteza Rohanian, Roya M. Hüppi, Farhad Nooralahzadeh +8
Capturing subtle speech disruptions across the psychosis spectrum is challenging because of the inherent variability in speech patterns. This variability reflects individual differ…
Radiology-Aware Model-Based Evaluation Metric for Report Generation
Amos Calamida, Farhad Nooralahzadeh, Morteza Rohanian +3
We propose a new automated evaluation metric for machine-generated radiology reports using the successful COMET architecture adapted for the radiology domain. We train and publish…
Boosting Radiology Report Generation by Infusing Comparison Prior
Sanghwan Kim, Farhad Nooralahzadeh, Morteza Rohanian +5
Recent transformer-based models have made significant strides in generating radiology reports from chest X-ray images. However, a prominent challenge remains: these models often la…
Improving the Cross-Lingual Generalisation in Visual Question Answering
Farhad Nooralahzadeh, Rico Sennrich
While several benefits were realized for multilingual vision-language pretrained models, recent benchmarks across various tasks and languages showed poor cross-lingual generalisati…
Progressive Transformer-Based Generation of Radiology Reports
Farhad Nooralahzadeh, Nicolas Perez Gonzalez, Thomas Frauenfelder +2
Inspired by Curriculum Learning, we propose a consecutive (i.e., image-to-text-to-text) generation framework where we divide the problem of radiology report generation into two ste…
Low-Resource Adaptation of Neural NLP Models
Farhad Nooralahzadeh
Real-world applications of natural language processing (NLP) are challenging. NLP models rely heavily on supervised machine learning and require large amounts of annotated data. Th…
Zero-Shot Cross-Lingual Transfer with Meta Learning
Farhad Nooralahzadeh, Giannis Bekoulis, Johannes Bjerva +1
Learning what to share between tasks has been a topic of great importance recently, as strategic sharing of knowledge has been shown to improve downstream task performance. This is…
Syntactic Dependency Representations in Neural Relation Classification
Farhad Nooralahzadeh, Lilja Øvrelid
We investigate the use of different syntactic dependency representations in a neural relation classification task and compare the CoNLL, Stanford Basic and Universal Dependencies s…
SIRIUS-LTG-UiO at SemEval-2018 Task 7: Convolutional Neural Networks with Shortest Dependency Paths for Semantic Relation Extraction and Classification in Scientific Papers
Farhad Nooralahzadeh, Lilja Øvrelid, Jan Tore Lønning
This article presents the SIRIUS-LTG-UiO system for the SemEval 2018 Task 7 on Semantic Relation Extraction and Classification in Scientific Papers. First we extract the shortest d…